Ten iterative steps for model development and evaluation applied to Computational Fluid Dynamics for Environmental Fluid Mechanics

Abstract

Computational Fluid Dynamics (CFD) is increasingly used to study a wide variety of complex Environmental Fluid Mechanics (EFM) processes, such as water flow and turbulent mixing of contaminants in rivers and estuaries and wind flow and air pollution dispersion in urban areas. However, the accuracy and reliability of CFD modeling and the correct use of CFD results can easily be compromised. In 2006, Jakeman et al. set out ten iterative steps of good disciplined model practice to develop purposeful, credible models from data and a priori knowledge, in consort with end-users, with every stage open to critical review and revision (Jakeman et al., 2006). This paper discusses the application of the ten-steps approach to CFD for EFM in three parts. In the first part, the existing best practice guidelines for CFD applications in this area are reviewed and positioned in the ten-steps framework. The second and third part present a retrospective analysis of two case studies in the light of the ten-steps approach: (1) contaminant dispersion due to transverse turbulent mixing in a shallow water flow and (2) coupled urban wind flow and indoor natural ventilation of the Amsterdam ArenA football stadium. It is shown that the existing best practice guidelines for CFD mainly focus on the last steps in the ten-steps framework. The reasons for this focus are outlined and the value of the additional - preceding - steps is discussed. The retrospective analysis of the case studies indicates that the ten-steps approach is very well applicable to CFD for EFM and that it provides a comprehensive framework that encompasses\ud and extends the existing best practice guidelines

CFD simulation of wind flow over natural complex terrain: Case study with validation by field measurements for Ria de Ferrol, Galicia, Spain

“…However, while such guidelines have been developed for RANS in the past 15 years (e.g. Casey and Wintergerste 2000, Franke et al 2004, 2007, Britter and Schatzmann 2007, Tominaga et al 2008, Schatzmann and Leitl 2011, Blocken and Gualtieri 2012, this is not the case for LES. This is turn is caused by the computational expense of LES, as the establishment of such guidelines requires extensive sensitivity tests.…”

“…Therefore, CFD verification and validation are imperative, and for this purpose, extensive sets of best practice guidelines for CFD in wind engineering have been developed in the past 15 years (e.g. Casey and Wintergerste 2000, Franke et al 2004, 2007, Britter and Schatzmann 2007, Tominaga et al 2008, Blocken and Gualtieri 2012, Blocken 2015. It should be noted that validation requires high-quality experimental data, either wind-tunnel data or field data, and these data in turn need to satisfy certain quality criteria (Schatzmann et al 1997, Schatzmann andLeitl 2011).…”

CFD simulation of pedestrian-level wind conditions around buildings: Past achievements and prospects

“…Several of these BPG documents were established specifically for the assessment of pedestrian-level wind conditions (Franke et al 2004, Blocken et al 2007, Tominaga et al 2008. Other, more general guidelines, but also of relevance to pedestrian-level wind conditions, are those by Casey and Wintergerste (2000), Jakeman et al (2006), Franke et al (2007 and Blocken and Gualtieri (2012). While papers focusing on guidelines are very important, they are not included in the VSI when they do not report specific CFD simulations.…”

Evaluation of a neighbourhood scale, street network dispersion model through comparison with wind tunnel data

“…In comparison with the methodology developed by Jakeman et al (2006) and applied, e.g., by Blocken and Gualtieri (2012) for CFD (Computational Fluid Dynamics) environmental models, the evaluation presented here covers part of the objectives included in the last two steps of the development and evaluation of an environmental model. The results presented here, complemented by those of other validations and analyses (e.g.…”